Automatic image annotation using group sparsity

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2010, Pages 3312-3319

  Zhang, Shaoting ^a   Huang, Junzhou ^a   Huang, Yuchi ^a   Yu, Yang ^a   Li, Hongsheng ^b   Metaxas, Dimitris N ^a  

^a RUTGERS UNIVERSITY   (United States)

^b Lehigh University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC IMAGE ANNOTATION; FEATURE COMBINATION; FEATURE SELECTION ALGORITHM; FEATURE SELECTION METHODS; IMAGE ANNOTATION; MODEL REPRESENTATION; PRE-SELECTED; RELEVANCE FEEDBACK;

COMPUTER VISION; FEEDBACK; IMAGE ANALYSIS;

FEATURE EXTRACTION;

EID: 77955998281     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2010.5540036     Document Type: Conference Paper

References (34)

1. A. Argyriou, T. Evgeniou, and M. Pontil. Multi-task feature learning. In NIPS, 2006.
2. K. Barnard, P. Duygulu, D. Forsyth, N. D. Freitas, D. M. Blei, J. K, T. Hofmann, T. Poggio, and J. Shawe-taylor. Matching words and pictures. Journal of Machine Learning Research, 3:1107-1135, 2003.
3. E. Berg, M. Schmidt, M. Friedlander, and K. Murphy. Group sparsity via linear-time projection. In Technical report, TR-2008-09, 2008.
4. G. Carneiro, A. B. Chan, P. J. Moreno, and N. Vasconcelos. Supervised learning of semantic classes for image annotation and retrieval. PAMI, 29(3):394-410, 2007.
5. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In CVPR, pages 886-893, 2005.
6. R. Datta, D. Joshi, J. Li, James, and Z. Wang. Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys, 39:2007, 2006.
7. P. Duygulu, K. Barnard, J. F. G. de Freitas, and D. A. Forsyth. Object recognition as machine translation: Learning a lexicon for a fixed image vocabulary. In ECCV, pages 97-112, 2002.
8. S. L. Feng, R. Manmatha, and V. Lavrenko. Multiple bernoulli relevance models for image and video annotation. In CVPR, 2004.
9. J. Goldberger, S. Roweis, G. Hinton, and R. Salakhutdinov. Neighbourhood components analysis. In NIPS, pages 513-520, 2004.
10. D. Grangier and S. Bengio. A discriminative kernel-based approach to rank images from text queries. PAMI, 30(8):1371-1384, 2008.
11. M. Grubinger, P. D. Clough, H. Muller, and T. Deselaers. The iapr tc-12 benchmark - a new evaluation resource for visual information systems. 2006.
12. M. Guillaumin, T. Mensink, J. Verbeek, and C. Schmid. Tagprop: Discriminative metric learning in nearest neighbor models for image auto-annotation. In ICCV, 2009.
13. R. Hadsell, S. Chopra, and Y. LeCun. Dimensionality reduction by learning an invariant mapping. In CVPR, pages 1735-1742, 2006.
14. T. Hertz, A. Bar-hillel, and D. Weinshall. Learning distance functions for image retrieval. In CVPR, pages 570-577, 2004.
15. X. Hou and L. Zhang. Saliency detection: A spectral residual approach. In CVPR, 2007.
16. J. Huang, X. Huang, and D. Metaxas. Learning with dynamic group sparsity. In ICCV, 2009.
17. J. Huang and T. Zhang. The benefit of group sparsity. In Technical Report arXiv:0901.2962, Rutgers University, 2009.
18. J. Jeon, V. Lavrenko, and R. Manmatha. Automatic image annotation and retrieval using cross-media relevance models. In ACM SIGIR, 2003.
19. V. Lavrenko, R. Manmatha, and J. Jeon. A model for learning the semantics of pictures. In NIPS, 2003.
20. J. Li and J. Wang. Real-time computerized annotation of pictures. PAMI, 30(6):985-002, 2008.
21. J. Liu, M. Li, Q. Liu, H. Lu, and S. Ma. Image annotation via graph learning. Pattern Recogn., 42(2):218-228, 2009.
22. D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60:91-110, 2004.
23. A. Makadia, V. Pavlovic, and S. Kumar. A new baseline for image annotation. In ECCV, pages 316-329, 2008.
24. D. Metzler and R. Manmatha. An inference network approach to image. In CIVR, pages 42-50, 2004.
25. F. Monay and D. Gatica-Perez. Plsa-based image autoannotation: Constraining the latent space. In ACM Multimedia, pages 348-351, 2004.
26. G. Obozinski, B.Taskar, and M. Jordan. Joint covariate selection and joint subspace selection for multiple classification problems. Statistics and Computing, 2009.
27. J. Pan, H. Yang, C. Faloutsos, and P. Duygulu. Automatic multimedia cross-modal correlation discovery, 2004.
28. M. Schmidt, K. Murphy, G. Fung, and R. Rosales. Structure learning in random fields for heart motion abnormality detection. In CVPR, 2008.
29. R. Tibshirani. Regression shrinkage and selection via the LASSO. Journal of the Royal Statistical Society, 58:267-288, 1994.
30. K. van de Sande, T. Gevers, and C. Snoek. Evaluating color descriptors for object and scene recognition. PAMI, 99(1).
31. O. Yakhnenko and V. Honavar. Annotating images and image objects using a hierarchical dirichlet process model. In MDM, pages 1-7, 2008.
32. A. Yavlinsky, E. Schofield, and S. Ruger. Automated image annotation using global features and robust nonparametric density estimation. In CIVR, pages 507-517, 2005.
33. M. Yuan and Y. Lin. Model selection and estimation in regression with grouped variables. Journal of the Royal Statistical Society, Series B, 68:49-67, 2006.
34. H. Zhang, A. C. Berg, M. Maire, and J. Malik. SVM-KNN: Discriminative nearest neighbor classification for visual category recognition. In CVPR, pages 2126-2136, 2006.